Multi-Level Perception Systems in Fusion of Lifeforms: Classification, Challenges and Future Conceptions.

Bingao Zhang, Xinyan You, Yiding Liu, Jingjing Xu, Shengyong Xu

Abstract readReview

In one paragraph

Review in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Bingao ZhangThe Key Laboratory for the Physics and Chemistry of Nanodevices, Institute of Physical Electronics, Department of Electronics, Peking University, Beijing 100871, China.ORCID 0009-0008-1269-3971

Xinyan YouSchool of Electronic and Information Engineering, Beihang University, Beijing 100191, China.

Yiding LiuThe Key Laboratory for the Physics and Chemistry of Nanodevices, Institute of Physical Electronics, Department of Electronics, Peking University, Beijing 100871, China.

Jingjing XuSchool of Integrated Circuits, Shandong University, Jinan 250010, China.ORCID 0000-0002-0443-547X

Shengyong XuThe Key Laboratory for the Physics and Chemistry of Nanodevices, Institute of Physical Electronics, Department of Electronics, Peking University, Beijing 100871, China.ORCID 0000-0001-9567-5980

Funding

the National Key R&D Program of China 2017YFA0701302the National Key R&D Program of China 2024YFC3406302the National Natural Science Foundation of China 12204273the Natural Science Foundation of Shandong Province, China ZR2024MF107

6 · The paper itself

Abstract

The emerging paradigm of "fusion of lifeforms" represents a transformative shift from conventional human-machine interfaces toward deeply integrated symbiotic systems, where biological and artificial components co-adapt structurally, energetically, informationally, and cognitively. This review systematically classifies multi-level perception systems within fusion of lifeforms into four functional categories: sensory and functional restoration, beyond-natural sensing, endogenous state sensing, and cognitive enhancement. We survey recent advances in neuroprosthetics, sensory augmentation, closed-loop physiological monitoring, and brain-computer interfaces, highlighting the transition from substitution to fusion. Despite significant progress, critical challenges remain, including multi-source heterogeneous integration, bandwidth and latency limitations, power and thermal constraints, biocompatibility, and system-level safety. We propose future directions such as layered in-body communication networks, sustainable energy strategies, advanced biointerfaces, and robust safety frameworks. Ethical considerations regarding self-identity, neural privacy, and legal responsibility are also discussed. This work aims to provide a comprehensive reference and roadmap for the development of next-generation fusion of lifeforms, ultimately steering human-machine integration from episodic functional repair toward sustained, multi-level symbiosis between biological and artificial systems.

Indexed as

PerceptionBrain-Computer InterfacesHumansIntelligent SystemsMan-Machine Systemsbrain–computer interfacecognitive enhancementfusion of lifeformshuman–machine integrationimplantable sensorsmulti-level perceptionneuroprostheticssensory restoration

Identifiers

PMID41600372

DOI10.3390/s26020576

PMCPMC12845757

What Socratic holds

Textmetadata

LicenceCC BY

Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.